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The regulatory effects of phosvitin phosphopeptide (PPP) and its calcium chelate (PPP-Ca) on osteoblast differentiation in the co-culture system of osteoblast (MC3T3-E1) and osteoclast precursor (RAW264.7) were investigated. Cytotoxicity, alkaline phosphatase (AKP) activity, tartrate-resistant acid phosphatase (TRAP) activity and TRAP staining were analyzed. The mRNA expressions of RANKL/OPG pathway-related proteins in osteoblasts were further studied by RT-PCR. The results showed that PPP and PPP-Ca increased theAKP activity in the MC3T3-E1 system by 9.5% and 12.7%, respectively. In the MC3T3-E1 system, PPP and PPP-ca increased the mRNA expression levels from 0.92 to 1.25 and 1.39, respectively, for OPG, and from 1.00 to 1.23 and 1.45, respectively for RANKL. The results of this study showed that PPP and PPP-ca could effectively promote the differentiation of osteoblasts. The experimental results provide a research basis for further exploration of the role of phosphopeptides in the multi-cell model system and the development of functional activity of phosphopeptides. [ABSTRACT FROM AUTHOR]

The aim of the research was to improve detection accuracy of the blood spots and meat spots in eggs, which can provide consumers with high-quality eggs. Spectroscopy technology and multiple classifier fusion for abnormal egg detection were investigated. Micro fiber spectrometer (Ocean Optics company, USB2000+) was used to collect the transmittance spectroscopy of both normal and abnormal eggs, which were from Hubei Shendan Healthy Food Co., Ltd. After outliers detection and elimination, there were 336 eggs in all, which were randomly assigned to training set and test set; among the 336 eggs, 224 (about two-thirds of the total) were assigned to the training set, and the remaining 112 (about one-third of the total) were assigned to the test set. Before multiple classifier fusion, all data collected from micro fiber spectrometer was preprocessed including the methods of SNV (standard normal variate), smoothing and MSC (multiplicative scatter correction). usion of multiple classifiers was used to detect the foreign bodies of eggs on the basis of single-classifier. Firstly, five single-classifiers which was inclusive of Naive Bayes classifier, Mahalanobis distance classifier, PLS-DA (partial least squares-discriminate analysis) classifier, AdaBoost (adaptive boosting) classifier and SVM (support vector machine) classifier were all trained, and five groups of classification results were attained. In order to choose suitable one from these five single-classifiers, according to diversity measure, output disagreement measure and error agreement measure were introduced and used, and Naive Bayes, AdaBoost and SVM classifiers were selected as the single-classifiers; then, on the basis of these three selected single-classifiers, through feature level fusion, 21 base-classifiers were obtained. In order to get the final base-classifiers which were used to accomplish the multiple classifier fusion, in a similar way, through output disagreement measure and error agreement measure again, 5 base-classifiers were chosen from these 21 base-classifiers. Finally, 5 basic-classifiers were fused by weight vote strategy on the decision level. The weight vote strategy was that each base-classifier was allocated a weight value according to its accuracy rate, and the higher accuracy rate a base-classifier had, the larger weight value it would be allocated, because it was more trusted. Detection accuracy rate of ensemble classifier, which was formed after multiple classifier fusion, was 92.86% and 91.07%, respectively for normal eggs and abnormal eggs. As a contrast, among all the single-classifiers and base-classifiers, the highest detection accuracy of normal eggs in the test set was 91.07%, which came from AdaBoost (500-600 nm), and the highest detection accuracy of abnormal eggs in the test set was 89.29%, which came from SVM (550-600 nm). The experiment results showed that the model established by multiple classifier fusion could take full advantage of the information which came from each single-classifier or base-classifier, and in the aspect of the detection accuracy of either normal eggs or abnormal eggs, the model established by multiple classifier fusion was indeed superior to the model established by each single-classifier or base-classifier. Even though the detection accuracy was enhanced by a small margin, considering that a large number of either normal eggs or abnormal eggs were being produced and being detected in lots of companies that were involved in eggs, in this meaning, the slight promotion of detection accuracy was of great significance. [ABSTRACT FROM AUTHOR]

Breathing is an important physiological activity of egg as a living organism, and it has a great influence on its storage, conveyance and incubation. Therefore, it is of great significance to study egg's breathing regularity and respiration intensity in a day and during its storage time in a month. In this paper, non-invasive micro-test technique (NMT) was used to real-time monitor O2 flux passing in and out the eggs through the eggshell and study the breathing regularity and the respiration intensity of the eggs. With this method, gas exchange (O2) was measured and it was confirmed that breathing indeed exists. In order to study egg's respiration in a day, a customized micro-testing examination platform was constructed for the real-time monitoring of the intensity and rate of oxygen exchange between an egg and its external environment at 4 time points (6:00, 12:00, 18:00, and 24:00). On the other hand, egg's O2 flux was measured at the same time in a day during a month as to seeking for breathing regularity in its storage time. It was indicated that the optimal distance of probe towards the egg surface was 50 μm and the blunt end of the egg was selected as the optimum measurement location via the pre-experiment. The results show that there are three breathing patterns of eggs, consuming O2, exhaust O2, and both including consuming and exhausting O2. After group A testing, it is concluded that both fertilized and non-fertilized eggs breathe strong at dawn and weak at noon regularly in a day and the respiration intensity of the two types of eggs perform difference at different time points. Fertilized eggs have more active physical activity and the process of metabolism than those of non-fertilized ones. Fertilized egg respiration shows significant difference (P<0.05) at noon and dawn in a day, but non-fertilized egg does not. In addition, after group B testing, it is intended that during storage time in a month, there exists two breathing peaks in its storage period in a month, and each peak appears at the eggs quality changing time. The second peak value exceeds the first peak value. It reveals that there's a unique breathing pattern of eggs that O2 respiration rate is high when life metabolism is active, and low when life metabolism is negative. Eggs laid lately are breathing relatively positive. This study can provide a reference for optimizing storage conditions, improving the hatchability of fertilized eggs and hatching egg embryo in further research. [ABSTRACT FROM AUTHOR]

An economical, effective and large-scale method for the preparation of immunoglobulin of chicken egg yolk (IgY) was developed. The method was based on an improved water dilution combining with polyethylene glycol 6000 (PEG6000) precipitation and anion-exchange chromatography. The egg yolk was diluted with 8 volumes of aseptic water, the pH of which was adjusted to 5.2 with 0.1 mol/L HCl, then the mixture was centrifuged at 5 000 x g after standing for 8 h at 4 degrees C. The crude IgY was obtained from the supernatant layer with the yield of 93.47%. The purification of IgY was achieved by 6% PEG6000 precipitation and DEAE-Toyo-pearl 650 M anion-exchange chromatographic packing. The optimum purified conditions by ion-exchange chromatography were as follows: equilibration with 0.05 mol/L phosphate buffer (pH 7.0) and elution with 0. 075 mol/L phosphate buffer (pH 7.0). The purity of the IgY fraction was consistently greater than 95% with high activity (73.77%) by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). This method is superior to the traditional ion-exchange chromatography that can't simultaneously obtain high purity and high recovery. Moreover, this method is suitable for a large-scale IgY preparation from chicken egg yolk.

We isolated the strain MBL13 with high collagenase productivity from the soil of piled up animal bones. It was identified as Bacillus cereus. We purified and characterized Bacillus cereus collagenase (BCC). The molecular weight of BCC was 38.0 kDa and the optimum temperature and pH for the enzyme activity were 40 degrees C and 8.0 respectively. The enzyme was stable when the temperature was below 50 degrees C, but only retained 10% activity when kept at 60 degrees C for 1 h. The enzyme activity was stable between pH 7.0-8.5. Some metal ions such as Ca2+, Zn2+, Mg2+ enhanced the enzyme activity, and Cu2+ brought the obvious inhibition. In addition, EDTA and EGTA could inhibit the enzyme activity. We suggested that the purified enzyme was a member of the metalloproteases. Based on the experiment of substrate specificity, we found that the purified enzyme was bone collagenolytic protease, and had a much stronger capacity of hydrolysis for type I collagen than that for type II collagen and type III collagen. By BCC hydrolyzing bone collagen, we obtained polypeptides with different chain lengths. The comparative test indicated that the hydrolysis capacity of BBC was higher than that of standard type I collagenase. The results introduced a new strain and a novel collagenolytic protease for industrial enzyme.